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Journal of Stress Physiology & Biochemistry, Vol. 9 No. 3 2013, pp. 169-180 ISSN 1997-0838Original Text Copyright © 2013 by Sofalian, Behi
ORIGINAL ARTICLE
Evaluating Freezing Resistance in Barley (Hordeum vulgare L.)
Using Molecular Markers and Some Physiological Traits
Omid Sofalian*, Maryam Behi
Plant Breeding Department, University of Mohaghegh Ardabili, Ardabil 179, Iran
*E-Mail: [email protected]
Received March 3, 2013
To evaluate the freezing resistance and genetic diversity in barley physiological traits, molecular markers and their relationship in 20 barley genotypes were assessed in field and greenhouse condition. The analysis of variance showed a significant difference among studied genotypes. The effect of acclimation temperature on prolin content, quantum efficiency of photosystem II, chlorophyll and soluble sugars content were studied as physiological traits. Freezing treatments were -4, -7, -10, -13 and -16 °C temperatures that applied in a 3 replicated randomized complete block design. Then their lethal temperature at which 50% of plant were died (LT50) was determined. To estimate FSI (Field Survival Index) index, the 20 genotypes were cultured in a separate experiment on field with 3 replications. The results showed negative significant correlation (-0.601) between field survival index and LT 50. Cluster analysis using physiological traits, genotypes of F-A1-1, F-A1-2, F-A2-11, F-GRB-85-5, Sahra, Sahand, Dasht and Makouei were categorized in a distinct group and had a high FSI and low LT 50. Makouei cultivar having LT50=-17.66°C and the highest percentage of winter survival in the field, was the most resistant genotype. 10 ISSR markers from 35 primers sequences were selected and used. These 9 ISSR primers produced 50 polymorphic bands. PIC and MI average index for all primers were 0.37 and 1.72 respectively. Cluster analysis of molecular data using Jaccard similarity coefficient categorized the genotypes to four distinct groups. Associations between molecular markers and traits were assessed by multiple regression analysis. Some informative markers related to FSI and also LT50 was determined. So it may be possible to use these markers for selection of resistant lines or genotypes in breeding programs.
Key words: Barley, Freezing resistance, genetic diversity, molecular marker, Physiological traits
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
Evaluating Freezing Resistance in Barley...
ORIGINAL ARTICLE
Evaluating Freezing Resistance in Barley (Hordeum vulgare L.)
Using Molecular Markers and Some Physiological Traits
Omid Sofalian*, Maryam Behi
Plant Breeding Department, University of Mohaghegh Ardabili, Ardabil 179, Iran
*E-Mail: [email protected]
Received March 3, 2013
To evaluate the freezing resistance and genetic diversity in barley physiological traits, molecular markers and their relationship in 20 barley genotypes were assessed in field and greenhouse condition. The analysis of variance showed a significant difference among studied genotypes. The effect of acclimation temperature on prolin content, quantum efficiency of photosystem II, chlorophyll and soluble sugars content were studied as physiological traits. Freezing treatments were -4, -7, -10, -13 and -16 °C temperatures that applied in a 3 replicated randomized complete block design. Then their lethal temperature at which 50% of plant were died (LT50) was determined. To estimate FSI (Field Survival Index) index, the 20 genotypes were cultured in a separate experiment on field with 3 replications. The results showed negative significant correlation (-0.601) between field survival index and LT 50. Cluster analysis using physiological traits, genotypes of F-A1-1, F-A1-2, F-A2-11, F-GRB-85-5, Sahra, Sahand, Dasht and Makouei were categorized in a distinct group and had a high FSI and low LT 50. Makouei cultivar having LT50=-17.66°C and the highest percentage of winter survival in the field, was the most resistant genotype. 10 ISSR markers from 35 primers sequences were selected and used. These 9 ISSR primers produced 50 polymorphic bands. PIC and MI average index for all primers were 0.37 and 1.72 respectively. Cluster analysis of molecular data using Jaccard similarity coefficient categorized the genotypes to four distinct groups. Associations between molecular markers and traits were assessed by multiple regression analysis. Some informative markers related to FSI and also LT50 was determined. So it may be possible to use these markers for selection of resistant lines or genotypes in breeding programs.
Key words: Barley, Freezing resistance, genetic diversity, molecular marker, Physiological traits
Between abiotic stresses, cold and freezing had
the most vulnerable effect to agriculture (Vagujfalvi
et al., 1999). During cold acclimation in fall
important biochemical and metabolic changes
occurred. As a result of acclimation plants stored
protective substance for freezing conditions
(Mahfoozi et al., 2005). Root in the annual winter
Cereals is the place of meristems that had been
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
153170
Sofalian, Behi
exposed to repair ability of cold and freezing
damages (Bridger et al., 1996). Sugars accumulation
such as Sucrose, Raffinose, Sorbitol and Fructan are
frequently observed during plants acclimation.
Some of these compounds caused protein and
membrane stability during dehydration that
occurred during freezing or drought condition
(Breton et al., 2000). Rong-hu et al. (2006) in a
study on barley cultivars showed that one quick and
indirect way to measure photosynthetic activity,
chlorophyll fluorescence and chlorophyll index are
estimation by SPAD (Bhardway and Singhal, 1981).
There are different ways to assessment of freezing
resistance in crop plants. Field evaluation method is
widely used for determine freezing tolerant in crop
plants. In this way filed survival index (FSI) is
noticeable and used as main index (Fowler, 1982).
Determining of the LT50 based on crown tissue is the
best method to estimate survival in the field,
because crown is the most susceptible part of
cereals and had a crucial role in regrowth after
winter (Gusta et al., 1982). Expression of a low
temperature tolerance gene is affected not only by
environment, but also by the poliotropic effects of
other genes or QTLs (Fowler, 2002). Today the
molecular marker systems is an effective tools and
serve as supplementary method for traditional
plant breeding that was mostly used in quantitative
traits selection programs (Lander and Botstein,
1987). Against molecular marker system, RAPD
marker had low repeatability and AFLP marker is
expensive and SSR required primary information
about target sequence, so ISSR marker system can
overcome these limitations and represent higher
level of polymorphism (Terzopoulos and Bebeli,
2008). Plant breeders are always followed by
genetic and biochemical markers using in
quantitative trait breeding programs. In this
experiment genetic diversity of some barley
cultivars were investigated using ISSR markers and
the relation of this marker loci with physiological
traits in associated with freezing resistance were
studied.
MATERIALS AND METHODS
This experiment was conducted in randomized
complete blocks with 3 replications in research field
of Mohaghegh Ardabili University in autumn of
2011. Plant materials that used in this study were
20 genotypes of improved barley (Table 1).
Additionally winter survival index (FSI) was
calculated separately. Also barley genotypes were
grown under greenhouse conditions. After 3-4 leaf
stage (2-3 week after planting), pots were
transferred from greenhouse to a growth chamber
and acclimated for 3 week in 4±1 °C. Then freezing
test was performed on crown region according to
methods of Limin and Fowler (1988) and Naghavi et
al., (2010). After temperature treatments (in 5
levels -4, -7, -10, -13 and -16 °C) were placed in
incubator with 4 °C for 24 hours. After 2 weeks
survived plants were counted and evaluated. Lethal
temperature for 50% was determined with probit
analysis. Measurements of soluble sugars were
done with method of (Irigoyen et al., 1992). As well
as proline concentration in leaf tissue was fully
developed and measured with (Bates et al., 1973)
method. Absorption rate of each solution was
recorded by spectrophotometry at a wavelength of
625 nm for soluble sugar and 520nm for proline.
Using standard solution for each of them and
regression relationship between concentration and
absorption, the soluble sugars rate of samples were
calculated on mg. proline concentration for each
sample is termed of micro gram proline in each
gram of leaf fresh weigh. Measurement of
chlorophyll fluorescence (Fv/Fm) was done with use
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
171
Evaluating Freezing Resistance in Barley...
fluorometer optic science os-30p USA. With using
special clamps, plant leafs placed in dark for 30
minutes then fluorescence of 3 genotypes was
evaluated. Chlorophyll content measurements were
done with SPAD-502. In order to reduce errors each
treatment were read 3 times, and means of them
were used for each treatment. DNA extraction was
done with CTAB (Saghai-Maroof et al., 1984). 9 ISSR
primers with suitable striped patterns and several
forms were selected for molecular analysis.
Polymerase chain reaction with the components
was listed in Table 2. Separation of amplified
products was conducted using agarose gel
electrophoresis with a concentration of 1.2 percent.
Staining of PCR products were done with using
Ethidium bromide. For statistical analysis SPSS 16
were used. Means of comparison was done with
LSD test in 5% of probability. Analysis if molecular
data were done using NTSYS2.2, GenAelex 6.4 and
PopGen 1.32 soft wares.
RESULTS AND DISCUSSION
Variance analysis of LT50 and FSI were shown in
Table 3. Between genotypes LT50 and FSI was
significant in 0.01 and 0.05 percent respectively.
Also analysis of variance of physiological traits was
shown in Table 4. Interaction of temperature and
genotype in soluble sugar and proline was
significant, for Chlorophyll content trait genotypes
was significant and for fluorescence rate (Fv/Fm)
interaction effect of genotype to temperature has
significant effect. Means comparison of genotypes
for FSI, LT50, Fv/Fm and chlorophyll amount was
shone in Table 5. According to results Makouei
cultivar with having minimum LT50 (-17.66) and the
highest amount of FSI (86.42%) is the most resistant
genotype, but genotype STIPA/PETUNIA1...(b) with
highest rate of LT50 (-5) and lowest rate of FSI
(59.44%) was the most sensitive genotype to
freezing. Genetic differences between genotypes in
barley have been reported by other researchers
(Fowler et al., 1981). The amount of Fv/Fm
decreased after acclimation. In the investigation of
cold acclimation period on quantum efficiency of
photosystem II in spring and winter oat varieties it
was founded that exposure these plants to
acclimation conditions, quantum efficiency level of
photosystem II decreased firstly but increased in
continue and then return to its first levels (Rizza et
al., 2001).
In the present study, there was not a certain
changes in chlorophyll content during thermal
stress but it can be observed that
STIPA/PETUNIA1...(b) STIPA/PETUNIA1...(c),
GLORIA-BAR/COPAL… and STIPA/PETUNIA1... (a)
genotypes have the lowest chlorophyll content.
These genotypes had somewhat lowest percent of
survival on a farm and had the highest amount of
LT50. Because of significant interaction effect of
soluble sugar and proline, means compassion
results is bring in Figure 1 and 2. Soluble sugars in
all genotypes increased in acclimation period
except for F-A-1-1 genotype. There were not
observed any specific trend between resistant
genotypes and susceptible ones in soluble sugars.
Livingston and Premakumar (2002) In study of
concentrations of soluble carbohydrate in crown
tissues of two oat cultivars that had different
reaction to two stages of acclimation, researchers
found that, in first stage of acclimation, apoplastic
liquid was consist of 2 percent of rot carbohydrates.
After one day placement in the second stage of
acclimation the percent of apoplast carbohydrates
increase to 0.5 percent of total carbohydrate of
root. They resulted that increasing apoplastic
carbohydrate is a mechanism that let winter cereals
to survive in freezing temperature. Prolin amount
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172
Sofalian, Behi
and survival percent before and after acclimation in
Makouei had the highest value and LT50 had lowest
amount. The lowest rates of proline had been
shown in genotype of 10 and before acclimation
that had the minimum surviving in field. According
to Figure 1 and 2 it can be stated that in most
genotypes proline increase after acclimation. Petcu
and Terbea (1995) reported that free proline
content in not acclimated plants is very little and
after two weeks in control condition this values
increased in all wheat genotypes. In this experiment
proline accumulation in the resistant genotype was
more than sensitive ones. The correlation between
LT50 and FSI was relatively high, negative and
statistically significant equal to (r=-0.601) (Table 6).
Prasil et al. (2007) in studying 39 cultivars of barley
showed that significant correlation between the
average five-year survivals and LT50 of field
condition and LT50 of acclimated plant in growth
chamber. There was positive and significant
correlation between chlorophyll content and FSI
(r=0.599). There was negative and significant
correlation between LT50 and chlorophyll
fluorescence amount after acclimation and prolin
amount after and before acclimation, r values was
respectively -0.504, -0.472, -0.493. Petcu and
Terbea, (1995) High correlation (-0.71) between
damage percentage of cold and proline content has
been reported in 50 genotype of winter wheat after
two weeks acclimation. According to cluster
analysis by physiological traits and LT50 (Figure 3),
genotypes of F-A1-1, F-A1-2, F-A2-11, F-GRB-85-5,
Sahra, Sahand, Dasht and Makouei were
categorized in a distinct group and had a high mean
for Prolin amount before and after acclimation,
chlorophyll content and FSI and low LT50. Nine
studied primers were produced 61 bands with
means of 6.78 bands per each primer. Among them
there was 11 monomorph band and 50 polymorphs
with means of 5.56 polymorphs band per each
primer. Polymorphism percent was ranged from
62.5 % for pp13 primer and 100 % for pp1 and pp9.
Means of polymorphism percent for all used primer
was 82.29 %. Primer banding pattern of pp19 is
shown in Figure 4. The polymorphism information
content (pic) for used primers in ISSR analysis was
varied from 0.29 in pp19 primer to 0.46 in pp9
(Table 7). PIC amount in this study showed the
primers performance in differential of used
genotype that can be advisable for similar studies.
Also marker index (MI) as an effective measure that
used for determine the polymorphism, was ranged
between 0.99 for pp16 primer and 3.51 for pp1 in
this study. In order to classification of barley
genotypes on the base of ISSR data, cluster analysis
was used with the method of complete linkage and
according to Jacquard similarity coefficient (Figure
5) and showed suitable grouping. Suitability of
cluster analysis was determined considering to
significant cophenetic correlation (0.68) in 1
percent of probability. In this analysis studied
genotypes were divided to four distinct groups. A
research was conducted on 16 barley cultivar with
using 10 ISSR markers (Fernandez, 2002). The
cluster analysis can easily conformed the well-
known barley origin also it can divide fall and spring
cultivars and Two and six-row of barley. ISSR
molecular markers relations were evaluated with
studied traits. In this stage stepwise regression was
performed for all traits (Table 8). Sugar solution
after habituation was associated with a marker with
corrected coefficient equal to 0.33. The lowest
variation was explained by markers. The marker of
pp5m7 had positive correlation with soluble sugar
content after acclimation. After regression analysis
for LT50, pp2m2, pp5m2 and pp19m3 markers was
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
126173
Evaluating Freezing Resistance in Barley...
interred to model with positive and pp2m5 and
pp16m4 with negative effects and can explain 94%
of variations. In FSI index, pp1m9 and pp19m3
markers with positive and pp1m8, pp19m2 and
pp19m5 with negative effects interred to model
and determined 94% of variations. Today’s using
correlation between molecular markers and
controlling genes for quantitative traits can
accelerate the process of plant breeding (Gebhardt,
2004).
Figure 1. Means comparison genotype acclimation using for soluble sugars content in studied barley
genotype
Figure 2. Means comparison genotype acclimation using for prolin content in studied barley
genotype
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
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Sofalian, Behi
Figure 3. Cluster analysis for physiological and LT50 traits using the Ward minimum variance method
Figure 4. The results of P.C.R. amplification were detected by means of agarose gel electrophoresis
Figure 5. Cluster analysis for ISSR data using the with the method of complete linkage and according
to Jacquard similarity coefficient
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
175
Evaluating Freezing Resistance in Barley...
Table 1. List of studied barley genotypes
GenotypeNumberGenotypeNumber
GLORIA-BAR/COPAL//BEN.4D/3/S.P-B/4/DC-B/SEN/5/CONGONA
11F-A1-11
STIPA/PETUNIA1//KOLLA/BBSC (a)12F-A1-22CHAMICO/TOCTE//CONGONA (a)13F-A2-113
PALLIDUM48//NORDIC/563.6.5/3/CEL-B…2/MZQ//CEL-B/5/LINO/6/CONGONA
14F-GRB-84-114
CHAMICO/TOCTE//CONGONA (d)15F-GRB-85-55Lesivi16PETUNIA1/CHINIA(a)6Sahra17CONGONA/BORR7Sahand18STIPA/PETUNIA1//KOLLA/BBSC(b)8
Dasht19PETUNIA1/CHINA (c)9
Lesivi20STIPA/PETUNIA1//KOLLA/BBSC (c)10
Table 2. PCRreaction contents for barley DNA samples propagation by using ISSR primers
1unit, (microliteres)contents
ISSR
2PCR buffer (1X)
0.8MgCl2(0.05Mm)
0.2dNTP(0.05mM)
1.6Primer
0.26Taq DNA polymerase
2DNA(25 ng)
11.4DdH2O
18μL Volume Total
Table 3. Analysis of variance for FSI & LT50 in studied barley genotype
MSdfSOV
LT50FSI9.64 ns**1645.862Repeat**35.86*262.1219Genotype4.36113.0138Error20.9815.44CV (%)
ns, * and **: non significance, significance at p<0.05 and significant at p<0.01 respectively
Table 4. Analysis of variance for physiological traits in studied barley genotype
MSdfSOV
Fv/FmChlorophyll contentProlinsoluble sugar content*0.014**156.99*0.005ns 0.112Repeat**0.247ns 5.8**1.314**17.351Acclimation**0.011**25.72**0.297**0.4219Genotype0.004 nsns 2.65**0.091**0.3219Genotype * Acclimation0.0043.450.0010.0578Error0.784.694.9719.18CV(%)
ns, * and **: non significance, significance at p<0.05 and significant at p<0.01 respectively
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
176
Sofalian, Behi
Table 5. Means comparison table for using studied barley genotype
LT50
( (C°FSI(%)
Fv/FmChlorophyll (SPAD)Genotype
-14.6877.350.82739.85F-A1-1
-15.5276.850.81740.43F-A1-2
-12.7069.550.82438.6F-A2-11
-8.3978.570.81639.1F-GRB-84-11
-13.6278.940.82239.67F-GRB-85-5
-7.6067.340.82042.08PETUNIA1/CHINIA(a)
-5.2273.440.81943.05CONGONA/BORR
-4.5759.440.81335.78STIPA/PETUNIA1...(b)
-8.8066.390.81839.8PETUNIA1/CHINA (c)
-7.5845.830.81136.25STIPA/PETUNIA1... (c)
-8.1852.180.82035.52GLORIA-BAR/COPAL…
-6.7262.220.81936.85STIPA/PETUNIA1... (a)
-7.8971.860.82339.97CHAMICO/TOCTE…(a)
-9.2165.140.82641.37PALLIDUM48…
-8.1372.220.81840.27CHAMICO/TOCTE... (d)
-9.0869.920.81341.13Lesivi
-10.6469.30.82440.3Sahra
-11.3465.250.81841.25Sahand
-11.5068.570.82240.83Dasht
-17.6686.420.82340.33Macouei
0.985.010.0150.717 %LSD(p<5)
Table 6. Correlation between physiological traits for studied barley genotypes
FSILT50
Soluble sugars content after acclima-tion
Soluble sugars content before acclima-tion
Chloro-phyll amount
Prolin amount after acclima-tion
Prolin amount before acclima-tion
Fv/Fm after acclima-tion
Fv/Fm before acclima-tion
SOV
1Fv/Fm before acclimation10.434Fv/Fm after acclimation
10.2830.136Prolin amount before acclimation1**0.565-0.083-0.125Prolin amount after acclimation
10.0290.235*0.4540.135Chlorophyll amount
1-0.021-0.0650.0140.3740.147Soluble sugars content before acclimation
10.116-0.173-0.233-0.0990.1380.260Soluble sugars content after acclimation
10.137-0.202-0.236*-0.493*-0.472*-0.504-0.297LT50
1**-0.601-0.0170.001**0.5990.1450.3980.3930.333FSI* and **: significance at p<0.05 and significant at p<0.01 respectively
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
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Evaluating Freezing Resistance in Barley...
Table 7. Primer sequences, polymorphic bands and PIC and MI values in ISSR analysis
Polymorphism (%)
Number of polymorphic fragments
Total number of fragments
MI(PIC)CodNumber of PrimerSequence 5’ to 3’
100993.510.39pp115’ AGAC AGACGC 3’
808102.240.35pp225’ GACAGACAGACA GACA 3’
83.33561.460.35pp555’ AACAACAACGC 3’
80451.280.40pp775’GAGAGAGAGAGAGAGAT 3’
100552.300.46pp995’ TCTCTCTCTCTCTCTCC 3’
62.5581.060.34pp13135’ ACACACACACACACACYG 3’
80450.990.31pp16165’ CACACACACACAAG 3’
83.33561.210.29pp19195’ AGAGAGAGAGAGAGAGT 3’
71.43571.460.41pp32325’ AGAGAGAGAGAGAGAC 3’
82.295.566.781.720.37Average
Table 8. Regression analysis based on physiological traits, LT50 and FSI using ISSR markers in studied barley genotypes
FSILT50
Soluble sugars content after acclimation
Chlorophyll amount
Prolin amount after acclimation
Prolin amount before acclimation
Fv/Fm after acclimation
markers
78.82-15.190.830.971.290.80.8Intercept-0.68-0.78pp1m8
0.371.1pp1m9
0.22pp2m2
-0.34pp2m5
1.61pp5m1
0.42pp5m2
-0.25pp5m4
0.40pp5m5
-0.63pp7m4
0.35pp9m2
-0.35pp9m5
-0.61-0.60pp16m1
-0.55-0.47pp16m2
-0.810.57pp16m4
-0.38-0.7pp19m1
-0.20pp19m2
0.490.480.25pp19m3
-0.53pp19m5
0.31pp32m1
0.940.940.330.670.870.560.93R2
CONCLUSION
The correlation between LT50 and traits are
relatively high, negative and significant at
probability level of one percent (r= 0.601). After
JOURNAL OF STRESS PHYSIOLOGY & BIOCHEMISTRY Vol. 9 No. 3 2013
178
Sofalian, Behi
regression analysis for LT50, pp5m2, pp2m2,
pp19m3 markers with positive effect and pp2m5
and pp16m4 with negative effect and nearly, 94% of
variance could have been explained. Therefore, the
negative regression coefficient markers are ideal
markers for LT50 and can be used for selection of
resistant genotypes for freezing. In FSI index,
pp1m9, pp19m3 markers with positive effect and
pp19m2, pp1m8, pp19m5 with negative effect
totally determined 94% variation. Therefore it could
deduce that ISSR molecular marker can be serving
as powerful marker system in the freezing tolerance
selection perspectives.
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